Jang-Hyun Kim

Artificial Intelligence · with Kim · 2019

A researcher in the Science corpus: 2 papers; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Jang-Hyun Kim trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Andrew L. Maas
  2. Yoshua Bengio
  3. Naoya Takahashi
  4. Xavier Glorot
  5. Yuxuan Wang
  6. Emmanuel Vincent
  7. Geoffrey E. Hinton
  8. Daniel W. Griffin
  9. Dong Yu
  10. Olaf Ronneberger

Who trusts Jang-Hyun Kim overall

  1. Sefik Emre Eskimez

Papers from Jang-Hyun Kim's perspective

Ordered by how strongly the researchers Jang-Hyun Kim trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Long Short-Term Memory
  2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  3. ImageNet classification with deep convolutional neural networks
  4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  5. Gradient-based learning applied to document recognition
  6. Attention is All you Need (Neural Information Processing Systems)
  7. Learning Multiple Layers of Features from Tiny Images
  8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  9. ImageNet: A large-scale hierarchical image database
  10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers